Department of Statistics and Actuarial Science
University of Waterloo
Waterloo, Ontario
CANADA N2L 3G1
(519) 888-4567, ext. 36987
FAX: (519) 746-1875
Email:
Office: M3 4007
Personal Homepage:
www.stats.uwaterloo.ca/%7Em3zhu/
Professor Zhu's current research interests include statistical machine learning, multivariate analysis, health informatics, predictive analytics, and data mining. His recent work has focused on efficient sparse kernel machines for unbalanced classification and rare target detection (e.g., LAGO), and the ensemble approach for variable selection (e.g., PGA). Professor Zhu has also made important theoretical contributions. For example, he was the first person to discover the theoretical difference between the forward and backward algorithms of projection pursuit, a popular dimension-reduction technique. The two algorithms were previously believed to be equivalent, and their nontrivial difference remained unknown in the statistics community for more than fifteen years until the publication of Professor Zhu's work in what is widely regarded as the top theoretical journal in the field of mathematical statistics.
Mu Zhu is an Associate Professor at the University of Waterloo (Waterloo, ON, Canada), and an Associate Editor of The American Statistician and The Canadian Journal of Statistics. A Phi Beta Kappa graduate of Harvard University (Cambridge, MA, USA), he has a PhD in statistics from Stanford University (Stanford, CA, USA). He is interested in statistical machine learning, multivariate analysis, health informatics, predictive analytics, and data mining. Born in China, educated in the United States, and a Canadian citizen, Dr. Zhu is married and lives with his wife and two children.